class_docstr: Tests gradients of multivariate unidimensional functions.
docstr: Tests gradients with multivariate sin and cosine.
docstr_tok: ["Tests","gradients","with","multivariate","sin","and","cosine","."]
code: def test_sin(self, tol):
      """Tests gradients with multivariate sin and cosine."""
      multi_var = lambda x: np.sin(x[0]) + np.cos(x[1])
      grad_multi_var = lambda x: np.array([np.cos(x[0]), -np.sin(x[1])])
  
      x_vec = [1.5, -2.5]
      g = qml.grad(multi_var, 0)
      auto_grad = g(x_vec)
      correct_grad = grad_multi_var(x_vec)
  
      assert np.allclose(auto_grad, correct_grad, atol=tol, rtol=0)
  
imports: import autograd
  import pytest
  import pennylane
  from pennylane import numpy
label_desc: Use image node_id 1 for calling the TestGradientMultiVar obj's underlying member method code with example usage: obj.test_sin(tol) without return types